flotation behavior of hard-to-separate and high-ash fine coal
TRANSCRIPT
http://dx.doi.org/10.5277/ppmp160215
Physicochem. Probl. Miner. Process. 52(2), 2016, 703−717 Physicochemical Problems
of Mineral Processing
www.minproc.pwr.wroc.pl/journal/ ISSN 1643-1049 (print)
ISSN 2084-4735 (online)
Received November 14, 2015; reviewed; accepted May 25, 2015
FLOTATION BEHAVIOR OF HARD-TO-SEPARATE
AND HIGH-ASH FINE COAL
Yaowen XING*, Xiahui GUI
**, Jiongtian LIU
**, Yijun CAO
**,
Yi ZHANG*, Shulei LI
*
* School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou
221116, Jiangsu, China **
Chinese National Engineering Research Center of Coal Preparation and Purification, China University of
Mining and Technology, Xuzhou 221116 , Jiangsu, China, [email protected]
Abstract: The flotation behavior of hard-to-separate and high-ash fine coal was investigated using
conventional flotation with constant power input. A new flotation process, based on energy input and
distribution, was designed to lower the ash content of concentrate. The results obtained using Fourier
transform infrared (FTIR) analysis show that the coal samples have good floatability because of many
hydrophobic and few hydrophilic functional groups. Under a constant power input, a large number of ash-
forming materials floated into a froth product at the start of flotation. Based on the Fuerstenau upgrading
curves, it was determined that the 0.25-0.074 mm size fraction range showed the worst selectivity when
compared with 0.50-0.25 mm and -0.074 mm size fractions. The desired concentrate with an ash content
of 13.98%, 27.59% of ash recovery, and 80.01% combustible matter recovery could be obtained by
transferring the excess energy of the flotation-conditioning stage to the pre-conditioning stage and
increasing the power input step-by-step in the flotation-conditioning stage at equal total energy
consumption.
Keywords: flotation behavior, fine coal, Fuerstenau upgrading curve, energy input, selectivity
Introduction
Froth flotation is an effective separation method for fine coal cleaning based on
differences in the surface hydrophobicity between the organic and mineral matters
(Vanangamudi et al., 1988; Tao et al., 2002; Barraza et al., 2013). However, when the
flotation difference between particles is either minimal or fine slimes content in coal
samples is high, conventional froth flotation methods mainly suffer from lack of
selectivity for fast-floating coals because of flotation of middlings and entrainment of
fines in the froth (Polat et al., 2003). To maximize coal production and utilization, coal
mining operations and preparations have been highly mechanized. It resulted in high
Y. Xing, X. Gui, J. Liu, Y. Cao, Y. Zhang, S. Li 704
proportions of ash matters in the raw coal, such as clays and middlings, which posed a
severe challenge to fine coal flotation (Jia et al., 2000; Xu, 2003; Tao et al., 2009).
High-efficiency flotation of hard-to-separate and high-ash slime has been a research
interest in China. It is necessary to search for a new method for enhancing the flotation
performance of hard-to-separate and high-ash fine coal. Many studies have been conducted to investigate the selectivity and kinetics of
hard-to-separate and high-ash fine coal flotation. Fines recovery by entrainment has a
detrimental effect on the flotation selectivity (Akdemir and Sonmez, 2003; Xu et al.,
2005; Wang and Peng, 2013; Liu and Peng, 2014). It is well known that the particle
size of fine coal is the most important parameter that effects the recovery and
entrainment behavior of coal and ash materials. It was shown recently by Gui et al.
(2014a, 2014b) that higher flotation efficiency index could be obtained through an
early low-energy input for the recovery of easy-to-float materials and late high-energy
input for the recovery of difficult-to-float materials. Entrainment could be significantly
depressed using a new flotation process based on the energy input and distribution
(Gui et al., 2014a; 2014b). Kinetics is an important aspect of fine coal flotation (Wills
and Napier-Munn, 2006; Li et al., 2012). The flotation rate determines the time needed
for removal of ash from raw coal. Coal particles with different sizes and densities have
different flotation rates. Most flotation rate tests show that the fine coal particles can
be described by the first-order kinetic model (Chelgani et al., 2010; Abkhoshk et al.,
2010). Moreover, Li et al. (2012) found that the combustible matter recovery could be
approximated with the first-order kinetic equation and flotation of ash forming
minerals by the second order equation. The flotation behavior of oxidized coals has
also been extensively studied (Dey, 2012; Xia et al., 2014). However, the complex
behavior of hard-to-separate and high-ash slime flotation is not well understood.
The present investigation was undertaken to search for an effective separation
method for hard-to-separate and high-ash slime. In this study, the flotation behavior of
different size fractions was analyzed. A new flotation process was designed based on
the energy input and distribution, and a comparison of flotation performance at
constant and variable power input was carried out.
Experimental
Materials
Dry fine coal samples were obtained from Wuhai City, Inner Mongolia, China. The
composition of the sample is shown in Table 1. The particle size is the main factor that
affects flotation of slime. A wet-screening test of the coal samples was conducted with
a set of standard sieves (0.500, 0.250, 0.125, 0.074, and 0.045 mm). The particle size
and ash content distributions are presented in Table 2. It indicates that the ash content
gradually increases as the particle size decreases. The yield and ash contents of the
fine-grained fractions are high. Fractions less than -0.074 mm account for 35.28% of
the yield with an ash content of 40.41%, which is 8.41% higher than the total ash
Flotation behavior of hard-to-separate and high-ash fine coal 705
content of samples. It should be noted that these fine fractions with high ash can easily
degrade concentrates through mechanical entrainment during the flotation process.
Table 1. Proximate analysis of coal samples (air dried)
Moisture ,% Volatile matter ,% Fixed carbon,% Ash ,%
2.37 15.79 48.73 33.11
Table 2. Particle size and ash content distributions of coal sample
Size fractions, mm Yield,% Ash,% Oversize Undersize
Yield,% Ash,% Yield,% Ash,%
0.50-0.25 16.38 29.16 16.38 29.16 100.00 31.99
0.25-0.125 32.85 26.25 49.24 27.22 83.62 32.55
0.125-0.074 15.49 28.01 64.72 27.41 50.76 36.63
0.074-0.045 10.08 34.52 74.80 28.37 35.28 40.41
-0.045 25.20 42.76 100.00 31.99 25.20 42.76
Total 100.00 31.99 - - - -
The density composition of the coal samples is presented in Table 3. It illustrates
that the yield of +1.8 g/cm3
is 27.10%, which is higher than those of the other
fractions. Coal at an intermediate density of fraction 1.5 g/cm3 to 1.8 g/cm
3 is 22.35%,
with an ash content reaching 30.26%. Theoretically, obtaining qualified product with
an ash content of 14% is not difficult because the density±0.1 content is lower than
20%.
Table 3. Density analysis data of samples
Density
fractions,
g/cm3
Yield,
%
Ash
content,
%
Cumulative of floating
objects
Cumulative of
sediments
Content of
density±0.1
Yield, % Ash, % Yield,% Ash, % Density,
g/cm3
Yield,
%
-1.3 10.08 3.16 10.08 3.16 100.00 31.34 1.30 29.37
-1.3+1.4 19.29 7.73 29.37 6.16 89.92 34.50 1.40 40.47
-1.4+1.5 21.18 15.00 50.55 9.87 70.63 41.81 1.50 33.13
-1.5+1.6 11.95 24.44 62.50 12.65 49.45 53.29 1.60 17.15
-1.6+1.8 10.40 36.96 72.90 16.12 37.50 62.48 1.70 10.40
+1.8 27.10 72.27 100.00 31.34 27.10 72.27 1.80 32.30
Total 100.00 31.34 - - - - - -
Fourier transform infrared (FTIR) spectra of coal samples with low-density
(< 1.5 g/cm3), moderate-density (1.5 g/cm
3 to 1.8 g/cm
3), and high-density
(> 1.8 g/cm3) fractions are shown in Fig. 1. The peak at 1030 cm
-1 is attributed to ash-
Y. Xing, X. Gui, J. Liu, Y. Cao, Y. Zhang, S. Li 706
bearing minerals, and the peaks at 3694 and 3618 cm-1
are attributed to kaolinite,
which is detrimental to flotation (Jia et al., 2000; Jena et al., 2008). The CH3 and CH2
groups were characterized by peaks approximately at 2850 cm-1
–2930 cm-1
and 1435
cm-1
. The peaks at 3420 and 1650 cm-1
are attributed to -OH and C=O groups,
respectively (Pietrzak and Wachowska, 2003; 2004; Grzybek et al., 2006; Xia and
Yang, 2013; Xia et al., 2013). The peak at 1596 cm-1
is attributed either to benzene
rings or to C=C. The peak at 915 cm-1
may be a phenolic hydroxyl group. The peaks at
800 –650 and 3030 cm-1
are attributed to C-H in aromatic and benzene rings. The
weak peaks of C=O and –OH and the considerably strong and sharp peaks of CH,
CH2, and CH3 suggest good floatability of the coal samples, which have relatively few
hydrophilic functional groups and a number of hydrophobic functional groups.
Nevertheless, coal particles with good hydrophobicity may lead to particle
aggregations because the particles are difficult to disperse in the flotation pulp, and
could result in the low selectivity as the ash materials are entrapped in the
agglomerated structure (Polat et al., 2003).
Fig. 1. FTIR spectra of coal samples with different density fractions
Method
Flotation rate tests were conducted in an XFDIII 0.75 dm3 laboratory flotation
machine. Kerosene and octanol were used as the collector and frother, respectively.
They are commonly used in industry. The impeller rotation speed, collector dosage,
frother dosage, solid content, and air flow rate were kept constant at 2100 rpm, 300
g/Mg, 100 g/ Mg, 100 g/ dm3, and 2.5 dm
3/min, respectively. Firstly, the pulp was pre-
wetted for 2 min. After that, first collector and then frother were added to the pulp.
The collector and frother conditioning periods were 1 and 0.5 min, respectively. The
flotation process was divided into four stages and continued for 3 min. Four flotation
concentrate products, namely, concentrate 1 (C1), concentrate 2 (C2), concentrate 3
(C3), and concentrate 4 (C4) were consecutively collected after 20, 40, 100, and 180 s,
respectively. Flotation concentrates and tailings were filtered, dried at 80°C and
Flotation behavior of hard-to-separate and high-ash fine coal 707
weighed. For the ash analysis, approximately 10 g of the dried sample from each
product was first ground using a mortar and pestle. Then, approximately 2 g of a
ground sample from each product was burned in an oven at 815 °C for 2 h. The
remaining ash was weighed to calculate the ash content (William et al., 2010).
Performance evaluation
The required ash content of clean coal in this experiment was 14%. The combustible
matter and ash recoveries, which are used to evaluate the flotation performance, were
calculated using the following general equations (Wills et al., 2006; Gupta et al.,
2009):
Combustible recovery (%) =(𝐹−𝑇)(100−𝐶)
(𝐶−𝑇)(100−𝐹)∙ 100 (1)
Ash recovery (%)=(F−T)C
(C−T)F∙ 100 (2)
where F, C, and T are the ash content of the feed, concentrates, and tailings,
respectively.
In this paper, the Fuerstenau upgrading curves are used for characterization,
comparison and analysis of the separation process. The curves are very useful in the
analysis of de-ashing and desulfurization of coal flotation results (Fuerstenau et al.,
1992). The kinetic equations relating the recoveries of two components in separation
products and time, when combined together to eliminate the time parameter, provide
Fuerstenau upgrading curves, which relate, for instance, the recoveries of two
components in concentrate. Additionally, there are simple empirical equations which
can be used to approximate the separation results (Drzymala and Ahmed, 2005;
Drzymala et al., 2010).
Results and discussion
Flotation behavior analysis using constant power input
The results of flotation kinetic experiments at the constant impeller rotation speed of
2100 rpm are shown in Table 4. The cumulated ash content, combustible matter and
ash recoveries increased as the flotation time increased. Clean coal with an ash content
of 19.03%, 43.19% of ash recovery, and 86.57% of combustible matter recovery can
be obtained with the flotation time up to 180 s, at which point the flotation process
was nearly completed. Interestingly, the ash content of concentrates rapidly increased
to 17.41%, which exceeded the required ash content of 14% within 20 s of flotation.
The ash recovery of the first concentrate C1 was 17.38%, which was much higher than
that of the others. This indicates that a large number of ash-forming materials floated
into the froth products at the onset of flotation, and completely deteriorated the
selectivity. The total ash of clean coals did not significantly increase as the flotation
Y. Xing, X. Gui, J. Liu, Y. Cao, Y. Zhang, S. Li 708
time increased from 20 s to 180 s. However, the floated ash content of the products
after 20 s remained at a high level. The ash contents of concentrates C2, C3, and C4
were 18.95, 20.10, and 23.15%, respectively. The ash recovery of C2, C3, and C4
decreased because the yield decreased. The results similar are to flotation of oxidized
coals. It is difficult to obtain a product with the ash content of 14%.
The flotation behavior of different particle sizes of the clean coal was also
investigated in this paper. As shown in Table 5, the recovery of all size fractions
decreased as the flotation proceeded. With a three-fold increase in flotation time, C3
recovery of -0.074 mm was higher than that of C2. Meanwhile, most materials in the
concentrate rapidly floated within 40 s of flotation, thus illustrating the high flotation
rate of coal samples. However, the ash content of all size fractions, totally exceeded
the initial product requirement for ash content of 14%, especially for the -0.125 mm
size fraction. Thus, the high ash content of cleans was the result of the flotation
behavior of all size fractions. The unliberated coarse particles floated and this was the
reason why the ash content of fraction of +0.125 mm was high. The high ash content
of the -0.125mm size fraction is likely attributed to nonselective flotation of a large
number of fine mud or ash particles. These high ash fractions floated into froth at the
beginning of flotation.
Table 4. Results of coal flotation
Products Ash
content,%
Combustible
matter
recovery,%
Ash
recovery,%
Cumulated
ash content,%
Cumulated
combustible
matter
recovery,%
Cumulated ash
recovery,%
C1 17.41 38.85 17.38 17.41 38.85 17.38
C2 18.95 19.40 9.63 17.93 58.25 27.01
C3 20.10 18.35 9.80 18.46 76.60 36.81
C4 23.15 9.98 6.38 19.03 86.57 43.19
Tailings 66.60 13.43 56.81 32.03 100.00 100.00
Total 32.03 100.00 100.00 - - -
Table 5. Results of different size fractions flotation
Products Combustible matter recovery,% Ash content,%
0.50-0.25 0.25-0.125 0.125-0.074 0.074-0.045 -0.045 0.50-0.25 0.25-0.125 0.125-0.074 0.074-0.045 -0.045
C1 36.82 43.32 49.51 29.72 28.76 15.92 16.91 16.99 19.15 19.95
C2 18.61 20.40 19.17 21.53 17.39 16.55 18.82 18.74 19.69 21.49
C3 18.31 16.64 16.61 25.08 19.61 15.35 18.22 20.64 20.26 24.82
C4 5.99 9.30 8.35 13.36 14.00 14.71 18.58 24.93 24.18 28.91
Tailings 20.27 10.34 6.36 10.31 20.24 56.32 61.06 73.10 74.28 71.43
Total 100.00 100.00 100.00 100.00 100.00 29.16 26.25 28.01 34.52 42.76
Flotation behavior of hard-to-separate and high-ash fine coal 709
To evaluate the separation process, a selective parameter from the Fuerstenau
recovery-recovery upgrading curve was used. A mathematical formula for the
approximation of the Fuerstenau curves could be derived from kinetic considerations.
Commonly, the flotation process can be explained as a rate process, because the rate
of recovery of either coal or ash particles is proportional to the concentration of either
coal or ash particles remaining in the pulp (Gupta et al., 2009). The classical first-
order equation was used to express the flotation kinetics of both the combustible
matter and ash recoveries:
𝜀 = 𝜀∞(1 − 𝑒−𝑘1𝑡) (3)
𝜀𝑎 = 𝜀𝑎∞(1 − 𝑒−𝑘2𝑡) (4)
where 𝜀 and 𝜀𝑎 are the combustible matter and ash recoveries in the concentrate,
respectively; 𝜀∞ and 𝜀𝑎∞ are the maximum combustible matter and ash recoveries in
the concentrate, respectively; 𝑘1 and 𝑘2 are the first order flotation rate constant of
combustible matter and ash forming material, respectively; and t is the flotation time.
Matlab7.0 was used to calculate the values of k1 and k2. The kinetics fitting results of
different size fractions are shown in Table 6.
Table 6. The kinetics fitting results of different size fractions
Materials Size fraction,mm 𝜀∞ 𝑘1 Correlation coefficient
square (R2)
Combustible
0.50-0.25 78.82 1.84 0.9939
0.25-0.125 86.96 1.99 0.9725
0.125-0.074 90.61 2.23 0.9638
0.074-0.045 91.02 1.19 0.9944
-0.045 79.16 1.27 0.9758
Total 84.38 1.76 0.9767
Size fraction,mm 𝜀𝑎∞ 𝑘2 Correlation coefficient
square (R2)
Ash
0.50-0.25 36.12 1.88 0.9959
0.25-0.125 53.00 1.86 0.9775
0.125-0.074 53.65 1.84 0.9556
0.074-0.045 44.67 1.05 0.9901
-0.045 33.62 0.91 0.9771
Total 42.27 1.50 0.9735
The combustible matter rate of the 0.25-0.074 mm size fraction was higher than
those of -0.074 mm fine fraction and +0.25 mm coarse fraction. This result can
probably be attributed to the low collision probability of fine particles and the high
detachment probability of coarse fraction. However, the ash materials rate decreased
with the particle size decreasing. It should be noted that the ash materials rate was
Y. Xing, X. Gui, J. Liu, Y. Cao, Y. Zhang, S. Li 710
only slightly lower than that of the combustible matter, which likely illustrates the
poor flotation selectivity. Table 6 also shows that a good fit for the flotation kinetics
results of both combustible and ash materials was obtained using the first order
dynamic model as the correlation coefficient square R2 values exceeded 0.9500. These
results agree well with other researchers (Vapur et al., 2010). Therefore, the
combinations of two first-order kinetic Eqs (3) and (4) gives :
𝜀 = 𝜀∞ [1 − (𝜀𝑎∞−𝜀𝑎
𝜀𝑎∞)
𝑘1𝑘2] . (5)
Assuming that 𝜀∞=𝜀𝑎∞=100% and =𝑘1
𝑘2 , which can evaluate separation selectivity,
then Eq (3-3) can be simplified to the following equation (Bakalarz and Drzymala,
2013):
𝜀 = 100 [1 − (100−𝜀𝑎
100)𝑘] . (6)
The fitting results of the Fuerstenau upgrading plots of different size fractions,
fixed starting and ending points are shown in Fig. 2 and Table 7. High R2 values were
obtained using Eq. (6), which indicates that the size range of 0.25-0.074 mm show the
worst selectivity compared with those of 0.50-0.25 and -0.074 mm size fractions. This
is probably due to high collision and low detachment probabilities of the middle-sized
fraction 0.25-0.074 mm with good hydrophobicity.
The phenomena observed above may be attributed to two factors: (i) an excessively
high-energy input during flotation, especially at the early stage, increased the number
of collisions among coal, ash-forming particles, and air bubbles, which led to the
mechanical entrapment and entrainment of ash with coal; and (ii) good hydrophobicity
of the coal samples based on the FTIR resulted in the formation of particle aggregates.
A large amount of ash particles were entrapped in the agglomerate structure, reducing
the flotation selectivity. A new flotation process based on energy input and
distribution was proposed to attempt to reduce the ash content of clean coal.
Table 7. Fitting results of different size fractions
Size fraction, mm 𝑘 Correlation coefficient square (R2)
0.50-0.25 2.97 0.9866
0.25-0.125 2.29 0.9892
0.125-0.074 2.60 0.9900
0.074-0.045 3.04 0.9850
-0.045 3.73 0.9970
Total Size 2.97 0.9913
Flotation behavior of hard-to-separate and high-ash fine coal 711
0 20 40 60 80 1000
20
40
60
80
100
Total size
0.50-0.25 mm
0.25-0.125 mm
0.125-0.074 mm
0.074-0.045 mm
-0.045 mm
Cu
mu
late
d c
om
bu
stib
le m
att
er
reco
ve
ry (
%)
Cumulated ash recovery in concentrate a(%)
Fig. 2. The Fuerstenau upgrading curve of different size fractions
Flotation process based on energy input and distribution
Experimental design
The total energy input in flotation is composed of pre-conditioning and flotation-
conditioning energy. Pre-conditioning was conducted for 210 s, and it involved pre-
wetting (120 s), collector (60 s) and frother (30 s) conditioning. Flotation was
conducted for 180 s. The flotation energy consumption test and energy input
calculation were performed according to the method proposed by Gui et al. (2014a).
Power data with different flotation shaft speeds are shown in Table 8. The new
flotation process design, based on energy input and distribution is as follows. Under
conditions of equal total energy consumption, the excess energy from the flotation-
conditioning stage was transferred to the pre-conditioning stage. The other conditions
were held constant. The impeller rotation speed was increased to 2500 rpm in the pre-
conditioning stage. The power input increased in the flotation-conditioning stage (900,
1200, 1500, and 1800 rpm at different flotation time). The total energy input under the
condition of energy input and distribution was 2898 J, which was similar to 2890 J
under constant power condition. The experimental design scheme is presented in Fig.
3. High pre-conditioning power input and high-shear conditioning can promote
dispersion of pulp and prevent excessive aggregation. However, the new energy input
pattern during the flotation-conditioning stage, where low energy was applied early
and high energy was applied late based on the floatability variation characteristics of
the materials, can improve the flotation selectivity.
Table 8. Power data with different flotation shaft speeds
n, rpm 300 600 900 1200 1500 1800 2100 2400 2500
P, W 0.17 0.29 0.53 0.75 1.29 3.49 7.41 10.20 11.98
Y. Xing, X. Gui, J. Liu, Y. Cao, Y. Zhang, S. Li 712
Fig. 3. Experimental design Fig. 4. Flotation results using variable
and constant power inputs
Flotation behavior analysis using variable power input
The kinetics flotation results using variable and constant power inputs are shown in
Fig. 4. Qualified clean coal with an ash content of 13.98%, ash recovery of 27.59%,
and 80.01% combustible matter recovery can be obtained. This indicates that a
variable-power input flotation pattern shows better selectivity and could lower the
concentrate ash content by 5.05%. The ash and combustible matter recoveries
decreased by 15.60 and 6.56%, respectively. However, the combustible matter
recovery remained above 80%, which is still acceptable in practical production.
Additionally, the Fuerstenau upgrading curves of variable power input and constant
power input are shown in Fig. 5. Obviously, the selectivity improved, as the k values
of variable power input and constant power input were 4.51 and 2.97, respectively.
A laser particle size analysis meter was used to measure the coal superficial size
distribution in the pulp at two different pre-conditioning power input conditions. The
circulation flow rate of laser particle size analysis meter was decreased to a minimum
to prevent damage to the agglomerate structure. Each sample was repeated 3 times.
The effect of pre-conditioning power input on the coal superficial size distribution in
the pulp is presented in Fig. 6. The coarse particles reduced while the fine fractions
increased. The superficial average size d50 decreased by 16.95 μm as the pre-
conditioning power input increased to 11.98 W. This illustrates that aggregations were
broken up by the high-shear pre-conditioning pattern. The ash particles entrapped in
the agglomerate structure were released. As a result, entrapment was controlled to a
lower degree. The flotation selectivity was improved.
Scanning electron microscopy (SEM) photographs of first concentrate C1 at two
different energy input patterns are shown in Fig. 7. Aggregations and ash materials
Flotation behavior of hard-to-separate and high-ash fine coal 713
significantly decreased on the surface of concentrate. This finding indicates that lower
ash content could be obtained by decreasing the total flotation-conditioning energy
and increasing the power, given that this energy pattern was suitable for floatability
variation characteristic of materials in the flotation-conditioning stage. The low-
energy input in the early stage of flotation decreased the number of collisions among
the coal, ash-forming particles, and air bubbles. Only easy-to-float materials with low
ash content could float using the low energy input in the early stage. Mechanical
entrapment and entrainment of ash with coal were suppressed. A qualified concentrate
could be obtained using a new flotation process by transferring the excess energy of
the flotation-conditioning stage to the pre-conditioning stage as well as increasing the
power input step by step in the flotation-conditioning stage under the condition of
equal total energy consumption.
0 20 40 60 80 100
0
20
40
60
80
100
Constant power input:
=100[1-((100-a)/100)2.97
],R2
=0.9913
Variable power input:
=100[1-((100-a)/100)4.51
],R2
=0.9958
••
Cu
mu
late
d c
om
bu
stib
le m
att
er
reco
ve
ry (
%)
Cumulated ash recovery in concentrate a(%)
Fig. 5. The Fuerstenau upgrading curve of variable power input and constant power input
Fig. 6. Effect of pre-conditioning power input on coal superficial size distribution in pulp
Y. Xing, X. Gui, J. Liu, Y. Cao, Y. Zhang, S. Li 714
Constant power input
Variable power input
Fig. 7. SEM pictures of concentrate C1 at two different energy input patterns
Conclusions
Based on FTIR analysis it can be said that coal samples exhibited good flotation
because of the presence of a large number of hydrophobic and few hydrophilic
functional groups,. A large number of ash-forming materials floated into froth
products at the beginning of flotation under constant power input. Ash content of all
size fractions exceeded the initial product requirement for ash of 14%. However, the
0.25-0.074 mm particles had the worst selectivity compared with that of 0.50-0.25 mm
and -0.074 mm, as determined from the Fuerstenau upgrading curves. These
observations could be attributed to the excessively high-energy input during the
flotation-conditioning stage, which increased the number of collisions among the coal,
ash-forming particles, and air bubbles that led to the mechanical entrapment and
entrainment of ash materials with coal. Moreover, the relatively good hydrophobicity
of the coal samples resulted in formation of particle aggregates, which reduced the
flotation selectivity of all size fractions.
Flotation behavior of hard-to-separate and high-ash fine coal 715
The desired concentrate could be obtained using a new flotation process by
transferring the excess energy from the flotation-conditioning stage to the pre-
conditioning stage and increasing the power input stepwise in the flotation-
conditioning stage under equal total energy consumption. A qualified clean coal with
an ash content of 13.98%, 27.59% of ash recovery, and 80.01% of combustible matter
recovery was obtained. The aggregates were broken up with a high-shear pre-
conditioning pattern based on laser particle size analysis. The new energy pattern in
the flotation-conditioning stage, low energy was applied early and high energy was
applied late. It was suitable for floatability variation characteristic of the materials.
Low-energy input in the early stage of flotation decreased the number of collisions
among coal, ash-forming particles, and air bubbles. Only easy-to-float materials with
the low ash content could float using the low energy input at the early stage.
Mechanical entrapment and entrainment of ash with coal particles was suppressed.
Acknowledgment
This research was supported by the Fundamental Research Funds for the Central Universities (Grant No.
2014QNA26) and a Project Funded by the Priority Academic Program Development of Jiangsu Higher
Education Institutions for which the authors express their appreciation.
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